Single Polyp Stats
Shayle Matsuda
10/28/2021
PERMANOVA for single polyp metabolomics
libraries
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## Sudarshan Shetty et al. <microbiome.github.io>##
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## transformLoad in data:
mData<-read.csv("single polyp master with PCoA coordinates.csv") #metabolomics data and xy coords from Ty
mData$ATTRIBUTE_Sample_Name<-as.factor(as.character(mData$ATTRIBUTE_Sample_Name))
mData$ATTRIBUTE_Colony_number<-as.factor(as.character(mData$ATTRIBUTE_Colony_number))
mData<-subset(mData, ATTRIBUTE_Colony_number!="976B")PERMANOVA
#PERMANOVA
#sep dfs
mData.sd<-mData[,1:11] #metadata
mData.meta<-mData[,12:566] #metabolomics data
# mData.PCoA<-mData[,567:568] #ty's x and y, but can't use these for STATS
# plot(mData.PCoA) #plot Ty's x and y, to confirm your distance matrix cooresponds right
####################### Between colonies and Between Sample points
# Bray-Curtis distance
mData.dist <- vegdist(mData[,12:566], method = "bray")
# write.csv(mData.dist, "mData.dist.csv")
PCOA <- pcoa(mData.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.dist2<-as.matrix(mData.dist)
mData.dist.sd<- inner_join(rownames_to_column(mData.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
############ plot Between colonies
BetweenColonies_plot<-ggplot(mData.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Colony_number), size = 4) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Colonies") +
theme_classic();BetweenColonies_plot
#PERMANOVA between COLONIES
set.seed(30)
adonis(mData.dist~ATTRIBUTE_Colony_number, data=mData.sd)##
## Call:
## adonis(formula = mData.dist ~ ATTRIBUTE_Colony_number, data = mData.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Colony_number 18 18.732 1.04064 32.641 0.64527 0.001 ***
## Residuals 323 10.297 0.03188 0.35473
## Total 341 29.029 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Colony_number 18 18.732 1.04064 32.641 0.64527 0.001 ***
# Residuals 323 10.297 0.03188 0.35473
# Total 341 29.029 1.00000
############# Between Sampling areas (polyps) ########
set.seed(30)
adonis(mData.dist~Area, data=mData.sd)##
## Call:
## adonis(formula = mData.dist ~ Area, data = mData.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## Area 5 0.7291 0.145811 1.7312 0.02511 0.017 *
## Residuals 336 28.3000 0.084226 0.97489
## Total 341 29.0290 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# Area 5 0.7291 0.145811 1.7312 0.02511 0.017 *
# Residuals 336 28.3000 0.084226 0.97489
# Total 341 29.0290 1.00000
adonis(mData.dist~Area*ATTRIBUTE_Colony_number, data=mData.sd)##
## Call:
## adonis(formula = mData.dist ~ Area * ATTRIBUTE_Colony_number, data = mData.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## Area 5 0.7291 0.14581 4.864 0.02511 0.001 ***
## ATTRIBUTE_Colony_number 18 18.7315 1.04064 34.712 0.64527 0.001 ***
## Area:ATTRIBUTE_Colony_number 90 2.7332 0.03037 1.013 0.09415 0.442
## Residuals 228 6.8353 0.02998 0.23546
## Total 341 29.0290 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# Area 5 0.7291 0.14581 4.864 0.02511 0.001 ***
# ATTRIBUTE_Colony_number 18 18.7315 1.04064 34.712 0.64527 0.001 ***
# Area:ATTRIBUTE_Colony_number 90 2.7332 0.03037 1.013 0.09415 0.445
# Residuals 228 6.8353 0.02998 0.23546
# Total 341 29.0290 1.00000
#Plot: No patterns
BetweenSampArea_plot<-ggplot(mData.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = Area), size = 4) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Sampling Area") +
theme_classic();BetweenSampArea_plot
Between polyps 1-3 only
# ########################### Between polyps 1-3 only
#subset data
mData.Polyps123<-subset(mData, Area=="Base"|Area=="Touching 1"|Area=="Touching 2")
mData.Polyps123.sd<-mData.Polyps123[,1:11]
# Bray-Curtis distance
mData.Polyps123.dist <- vegdist(mData.Polyps123[,12:566], method = "bray")
PCOA <- pcoa(mData.Polyps123.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Polyps123.dist.sd<- inner_join(rownames_to_column(mData.Polyps123.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Polyps123.dist~Area, data=mData.Polyps123.sd)##
## Call:
## adonis(formula = mData.Polyps123.dist ~ Area, data = mData.Polyps123.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## Area 2 0.0603 0.030125 0.33161 0.00393 0.992
## Residuals 168 15.2620 0.090846 0.99607
## Total 170 15.3223 1.00000# Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# Area 2 0.0603 0.030125 0.33161 0.00393 0.992
# Residuals 168 15.2620 0.090846 0.99607
# Total 170 15.3223 1.00000
set.seed(30)
adonis(mData.Polyps123.dist~Area*ATTRIBUTE_Colony_number, data=mData.Polyps123.sd)##
## Call:
## adonis(formula = mData.Polyps123.dist ~ Area * ATTRIBUTE_Colony_number, data = mData.Polyps123.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## Area 2 0.0603 0.03013 0.9495 0.00393 0.466
## ATTRIBUTE_Colony_number 18 10.7537 0.59743 18.8308 0.70183 0.001 ***
## Area:ATTRIBUTE_Colony_number 36 0.8916 0.02477 0.7806 0.05819 0.986
## Residuals 114 3.6168 0.03173 0.23605
## Total 170 15.3223 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# Area 2 0.0603 0.03013 0.9495 0.00393 0.460
# ATTRIBUTE_Colony_number 18 10.7537 0.59743 18.8308 0.70183 0.001 ***
# Area:ATTRIBUTE_Colony_number 36 0.8916 0.02477 0.7806 0.05819 0.983
# Residuals 114 3.6168 0.03173 0.23605
# Total 170 15.3223 1.00000
#Plot by Colony number (see that still cluster by colony)
BetweenPoly123_plot<-ggplot(mData.Polyps123.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Colony_number), size = 4) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Polyps 1-3") +
theme_classic();BetweenPoly123_plot
#Plot by Polyp number (see that no cluster)
BetweenPoly123_plot2<-ggplot(mData.Polyps123.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = Area), size = 4) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Polyps 1-3 by polyp#") +
theme_classic();BetweenPoly123_plot2
Between Branches by individual colony
#Between Branches by colony ###########################
####### colony 945 #######
mData.Branch945<-subset(mData, ATTRIBUTE_Colony_number=="945")
#subset data
mData.Branch945.sd<-mData.Branch945[,1:11]
# Bray-Curtis distance
mData.Branch945.dist <- vegdist(mData.Branch945[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch945.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch945.dist.sd<- inner_join(rownames_to_column(mData.Branch945.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch945.dist~Area, data=mData.Branch945.sd)##
## Call:
## adonis(formula = mData.Branch945.dist ~ Area, data = mData.Branch945.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## Area 5 0.16096 0.032193 0.96577 0.28694 0.505
## Residuals 12 0.40001 0.033334 0.71306
## Total 17 0.56097 1.00000# Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# Area 5 0.16096 0.032193 0.96577 0.28694 0.499
# Residuals 12 0.40001 0.033334 0.71306
# Total 17 0.56097 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch945_plot<-ggplot(mData.Branch945.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size = 2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 945") +
theme_classic();Branch945_plot
####### colony 957 #######
mData.Branch957<-subset(mData, ATTRIBUTE_Colony_number=="957")
#subset data
mData.Branch957.sd<-mData.Branch957[,1:11]
# Bray-Curtis distance
mData.Branch957.dist <- vegdist(mData.Branch957[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch957.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch957.dist.sd<- inner_join(rownames_to_column(mData.Branch957.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch957.dist~Area, data=mData.Branch957.sd)##
## Call:
## adonis(formula = mData.Branch957.dist ~ Area, data = mData.Branch957.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## Area 5 0.084667 0.016933 1.1214 0.31845 0.303
## Residuals 12 0.181202 0.015100 0.68155
## Total 17 0.265869 1.00000# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# Area 5 0.084667 0.016933 1.1214 0.31845 0.303
# Residuals 12 0.181202 0.015100 0.68155
# Total 17 0.265869 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch957_plot<-ggplot(mData.Branch957.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size = 2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 957") +
theme_classic();Branch957_plot
####### colony 959 #######
mData.Branch959<-subset(mData, ATTRIBUTE_Colony_number=="959")
#subset data
mData.Branch959.sd<-mData.Branch959[,1:11]
# Bray-Curtis distance
mData.Branch959.dist <- vegdist(mData.Branch959[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch959.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch959.dist.sd<- inner_join(rownames_to_column(mData.Branch959.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch959.dist~Area, data=mData.Branch959.sd)##
## Call:
## adonis(formula = mData.Branch959.dist ~ Area, data = mData.Branch959.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## Area 5 0.071079 0.014216 1.0094 0.29607 0.464
## Residuals 12 0.168995 0.014083 0.70393
## Total 17 0.240074 1.00000# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# Area 5 0.084667 0.016933 1.1214 0.31845 0.303
# Residuals 12 0.181202 0.015100 0.68155
# Total 17 0.265869 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch959_plot<-ggplot(mData.Branch959.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size = 2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 959") +
theme_classic();Branch959_plot
####### colony 960 #######
mData.Branch960<-subset(mData, ATTRIBUTE_Colony_number=="960")
#subset data
mData.Branch960.sd<-mData.Branch960[,1:11]
# Bray-Curtis distance
mData.Branch960.dist <- vegdist(mData.Branch960[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch960.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch960.dist.sd<- inner_join(rownames_to_column(mData.Branch960.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch960.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch960.sd)##
## Call:
## adonis(formula = mData.Branch960.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch960.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.05525 0.027625 1.4696 0.16384 0.164
## Residuals 15 0.28196 0.018798 0.83616
## Total 17 0.33721 1.00000# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.05525 0.027625 1.4696 0.16384 0.164
# Residuals 15 0.28196 0.018798 0.83616
# Total 17 0.33721 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch960_plot<-ggplot(mData.Branch960.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size = 2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 960") +
theme_classic();Branch960_plot
####### colony 961 Sig#######
mData.Branch961<-subset(mData, ATTRIBUTE_Colony_number=="961")
#subset data
mData.Branch961.sd<-mData.Branch961[,1:11]
# Bray-Curtis distance
mData.Branch961.dist <- vegdist(mData.Branch961[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch961.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch961.dist.sd<- inner_join(rownames_to_column(mData.Branch961.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch961.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch961.sd)##
## Call:
## adonis(formula = mData.Branch961.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch961.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.12052 0.060262 2.7776 0.27026 0.022 *
## Residuals 15 0.32543 0.021695 0.72974
## Total 17 0.44595 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.12052 0.060262 2.7776 0.27026 0.03 *
# Residuals 15 0.32543 0.021695 0.72974
# Total 17 0.44595 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch961_plot<-ggplot(mData.Branch961.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 961") +
theme_classic();Branch961_plot
####### colony 962 Significant #######
mData.Branch962<-subset(mData, ATTRIBUTE_Colony_number=="962")
#subset data
mData.Branch962.sd<-mData.Branch962[,1:11]
# Bray-Curtis distance
mData.Branch962.dist <- vegdist(mData.Branch962[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch962.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch962.dist.sd<- inner_join(rownames_to_column(mData.Branch962.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch962.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch962.sd)##
## Call:
## adonis(formula = mData.Branch962.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch962.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.23235 0.11618 2.3623 0.23953 0.011 *
## Residuals 15 0.73770 0.04918 0.76047
## Total 17 0.97005 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# ATTRIBUTE_Branch_Letter 2 0.23235 0.11618 2.3623 0.23953 0.016 *
# Residuals 15 0.73770 0.04918 0.76047
# Total 17 0.97005 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch962_plot<-ggplot(mData.Branch962.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 962") +
theme_classic();Branch962_plot
####### colony 963 Sig #######
mData.Branch963<-subset(mData, ATTRIBUTE_Colony_number=="963")
#subset data
mData.Branch963.sd<-mData.Branch963[,1:11]
# Bray-Curtis distance
mData.Branch963.dist <- vegdist(mData.Branch963[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch963.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch963.dist.sd<- inner_join(rownames_to_column(mData.Branch963.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch963.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch963.sd)##
## Call:
## adonis(formula = mData.Branch963.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch963.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.072242 0.036121 4.0202 0.34897 0.004 **
## Residuals 15 0.134771 0.008985 0.65103
## Total 17 0.207013 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.072242 0.036121 4.0202 0.34897 0.004 **
# Residuals 15 0.134771 0.008985 0.65103
# Total 17 0.207013 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch963_plot<-ggplot(mData.Branch963.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 963") +
theme_classic();Branch963_plot
####### colony 964 #######
mData.Branch964<-subset(mData, ATTRIBUTE_Colony_number=="964")
#subset data
mData.Branch964.sd<-mData.Branch964[,1:11]
# Bray-Curtis distance
mData.Branch964.dist <- vegdist(mData.Branch964[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch964.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch964.dist.sd<- inner_join(rownames_to_column(mData.Branch964.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch964.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch964.sd)##
## Call:
## adonis(formula = mData.Branch964.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch964.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.06878 0.034389 0.56486 0.07004 0.901
## Residuals 15 0.91322 0.060881 0.92996
## Total 17 0.98200 1.00000# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.06878 0.034389 0.56486 0.07004 0.901
# Residuals 15 0.91322 0.060881 0.92996
# Total 17 0.98200 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch964_plot<-ggplot(mData.Branch964.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 964") +
theme_classic();Branch964_plot
####### colony 965 #######
mData.Branch965<-subset(mData, ATTRIBUTE_Colony_number=="965")
#subset data
mData.Branch965.sd<-mData.Branch965[,1:11]
# Bray-Curtis distance
mData.Branch965.dist <- vegdist(mData.Branch965[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch965.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch965.dist.sd<- inner_join(rownames_to_column(mData.Branch965.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch965.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch965.sd)##
## Call:
## adonis(formula = mData.Branch965.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch965.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.035052 0.017526 1.6975 0.18456 0.096 .
## Residuals 15 0.154870 0.010325 0.81544
## Total 17 0.189922 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# # # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.035052 0.017526 1.6975 0.18456 0.096 .
# Residuals 15 0.154870 0.010325 0.81544
# Total 17 0.189922 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch965_plot<-ggplot(mData.Branch965.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 965") +
theme_classic();Branch965_plot
####### colony 966 #######
mData.Branch966<-subset(mData, ATTRIBUTE_Colony_number=="966")
#subset data
mData.Branch966.sd<-mData.Branch966[,1:11]
# Bray-Curtis distance
mData.Branch966.dist <- vegdist(mData.Branch966[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch966.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch966.dist.sd<- inner_join(rownames_to_column(mData.Branch966.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch966.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch966.sd)##
## Call:
## adonis(formula = mData.Branch966.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch966.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.09030 0.045150 1.6735 0.18243 0.063 .
## Residuals 15 0.40469 0.026979 0.81757
## Total 17 0.49499 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.09030 0.045150 1.6735 0.18243 0.063 .
# Residuals 15 0.40469 0.026979 0.81757
# Total 17 0.49499 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch966_plot<-ggplot(mData.Branch966.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 966") +
theme_classic();Branch966_plot
####### colony 967 Sig #######
mData.Branch967<-subset(mData, ATTRIBUTE_Colony_number=="967")
#subset data
mData.Branch967.sd<-mData.Branch967[,1:11]
# Bray-Curtis distance
mData.Branch967.dist <- vegdist(mData.Branch967[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch967.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch967.dist.sd<- inner_join(rownames_to_column(mData.Branch967.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch967.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch967.sd)##
## Call:
## adonis(formula = mData.Branch967.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch967.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.063923 0.031961 2.1131 0.21981 0.007 **
## Residuals 15 0.226880 0.015125 0.78019
## Total 17 0.290802 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.063923 0.031961 2.1131 0.21981 0.007 **
# Residuals 15 0.226880 0.015125 0.78019
# Total 17 0.290802 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch967_plot<-ggplot(mData.Branch967.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 967") +
theme_classic();Branch967_plot
####### colony 968 Sig #######
mData.Branch968<-subset(mData, ATTRIBUTE_Colony_number=="968")
#subset data
mData.Branch968.sd<-mData.Branch968[,1:11]
# Bray-Curtis distance
mData.Branch968.dist <- vegdist(mData.Branch968[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch968.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch968.dist.sd<- inner_join(rownames_to_column(mData.Branch968.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch968.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch968.sd)##
## Call:
## adonis(formula = mData.Branch968.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch968.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.13431 0.067156 1.9566 0.2069 0.04 *
## Residuals 15 0.51484 0.034323 0.7931
## Total 17 0.64915 1.0000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# # # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.13431 0.067156 1.9566 0.2069 0.04 *
# Residuals 15 0.51484 0.034323 0.7931
# Total 17 0.64915 1.0000
#Plot by Colony number (see that still cluster by colony)
Branch968_plot<-ggplot(mData.Branch968.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 968") +
theme_classic();Branch968_plot
####### colony 969 #######
mData.Branch969<-subset(mData, ATTRIBUTE_Colony_number=="969")
#subset data
mData.Branch969.sd<-mData.Branch969[,1:11]
# Bray-Curtis distance
mData.Branch969.dist <- vegdist(mData.Branch969[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch969.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch969.dist.sd<- inner_join(rownames_to_column(mData.Branch969.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch969.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch969.sd)##
## Call:
## adonis(formula = mData.Branch969.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch969.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.05642 0.028210 1.1902 0.13695 0.276
## Residuals 15 0.35554 0.023703 0.86305
## Total 17 0.41196 1.00000# # # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.05642 0.028210 1.1902 0.13695 0.276
# Residuals 15 0.35554 0.023703 0.86305
# Total 17 0.41196 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch969_plot<-ggplot(mData.Branch969.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 969") +
theme_classic();Branch969_plot
####### colony 971 #######
mData.Branch971<-subset(mData, ATTRIBUTE_Colony_number=="971")
#subset data
mData.Branch971.sd<-mData.Branch971[,1:11]
# Bray-Curtis distance
mData.Branch971.dist <- vegdist(mData.Branch971[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch971.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch971.dist.sd<- inner_join(rownames_to_column(mData.Branch971.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch971.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch971.sd)##
## Call:
## adonis(formula = mData.Branch971.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch971.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.07725 0.038623 1.1665 0.1346 0.339
## Residuals 15 0.49665 0.033110 0.8654
## Total 17 0.57390 1.0000# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.07725 0.038623 1.1665 0.1346 0.339
# Residuals 15 0.49665 0.033110 0.8654
# Total 17 0.57390 1.0000
#Plot by Colony number (see that still cluster by colony)
Branch971_plot<-ggplot(mData.Branch971.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 971") +
theme_classic();Branch971_plot
####### colony 974 Sig #######
mData.Branch974<-subset(mData, ATTRIBUTE_Colony_number=="974")
#subset data
mData.Branch974.sd<-mData.Branch974[,1:11]
# Bray-Curtis distance
mData.Branch974.dist <- vegdist(mData.Branch974[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch974.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch974.dist.sd<- inner_join(rownames_to_column(mData.Branch974.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch974.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch974.sd)##
## Call:
## adonis(formula = mData.Branch974.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch974.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.065853 0.032926 3.0197 0.28705 0.001 ***
## Residuals 15 0.163557 0.010904 0.71295
## Total 17 0.229409 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.065853 0.032926 3.0197 0.28705 0.001 ***
# Residuals 15 0.163557 0.010904 0.71295
# Total 17 0.229409 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch974_plot<-ggplot(mData.Branch974.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 974") +
theme_classic();Branch974_plot
####### colony 976 #######
mData.Branch976<-subset(mData, ATTRIBUTE_Colony_number=="976")
#subset data
mData.Branch976.sd<-mData.Branch976[,1:11]
# Bray-Curtis distance
mData.Branch976.dist <- vegdist(mData.Branch976[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch976.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch976.dist.sd<- inner_join(rownames_to_column(mData.Branch976.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch976.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch976.sd)##
## Call:
## adonis(formula = mData.Branch976.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch976.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.19834 0.099168 1.6206 0.17769 0.128
## Residuals 15 0.91786 0.061191 0.82231
## Total 17 1.11620 1.00000# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.19834 0.099168 1.6206 0.17769 0.128
# Residuals 15 0.91786 0.061191 0.82231
# Total 17 1.11620 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch976_plot<-ggplot(mData.Branch976.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 976") +
theme_classic();Branch976_plot
####### colony 978 #######
mData.Branch978<-subset(mData, ATTRIBUTE_Colony_number=="978")
#subset data
mData.Branch978.sd<-mData.Branch978[,1:11]
# Bray-Curtis distance
mData.Branch978.dist <- vegdist(mData.Branch978[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch978.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch978.dist.sd<- inner_join(rownames_to_column(mData.Branch978.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch978.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch978.sd)##
## Call:
## adonis(formula = mData.Branch978.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch978.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.05551 0.027757 1.2815 0.14593 0.27
## Residuals 15 0.32490 0.021660 0.85407
## Total 17 0.38042 1.00000# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.05551 0.027757 1.2815 0.14593 0.27
# Residuals 15 0.32490 0.021660 0.85407
# Total 17 0.38042 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch978_plot<-ggplot(mData.Branch978.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 978") +
theme_classic();Branch978_plot
####### colony 983 #######
mData.Branch983<-subset(mData, ATTRIBUTE_Colony_number=="983")
#subset data
mData.Branch983.sd<-mData.Branch983[,1:11]
# Bray-Curtis distance
mData.Branch983.dist <- vegdist(mData.Branch983[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch983.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch983.dist.sd<- inner_join(rownames_to_column(mData.Branch983.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch983.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch983.sd)##
## Call:
## adonis(formula = mData.Branch983.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch983.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.21713 0.108565 1.0892 0.12681 0.367
## Residuals 15 1.49516 0.099677 0.87319
## Total 17 1.71229 1.00000# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.21713 0.108565 1.0892 0.12681 0.367
# Residuals 15 1.49516 0.099677 0.87319
# Total 17 1.71229 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch983_plot<-ggplot(mData.Branch983.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 983") +
theme_classic();Branch983_plot
####### colony 984 #######
mData.Branch984<-subset(mData, ATTRIBUTE_Colony_number=="984")
#subset data
mData.Branch984.sd<-mData.Branch984[,1:11]
# Bray-Curtis distance
mData.Branch984.dist <- vegdist(mData.Branch984[,12:566], method = "bray")
PCOA <- pcoa(mData.Branch984.dist) #pcoa
barplot(PCOA$values$Relative_eig[1:10]) # plot the eigenvalues 
biplot.pcoa(PCOA) #plot
PCOAaxes <- PCOA$vectors[,c(1,2)] #for visualization only
mData.Branch984.dist.sd<- inner_join(rownames_to_column(mData.Branch984.sd), rownames_to_column(data.frame(PCOAaxes)), type = "right", by = "rowname") #merge PCOAaxes and metadata
set.seed(30)
adonis(mData.Branch984.dist~ATTRIBUTE_Branch_Letter, data=mData.Branch984.sd)##
## Call:
## adonis(formula = mData.Branch984.dist ~ ATTRIBUTE_Branch_Letter, data = mData.Branch984.sd)
##
## Permutation: free
## Number of permutations: 999
##
## Terms added sequentially (first to last)
##
## Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
## ATTRIBUTE_Branch_Letter 2 0.044803 0.022402 1.7273 0.18719 0.091 .
## Residuals 15 0.194538 0.012969 0.81281
## Total 17 0.239341 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# # Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
# ATTRIBUTE_Branch_Letter 2 0.044803 0.022402 1.7273 0.18719 0.091 .
# Residuals 15 0.194538 0.012969 0.81281
# Total 17 0.239341 1.00000
#Plot by Colony number (see that still cluster by colony)
Branch984_plot<-ggplot(mData.Branch984.dist.sd, aes(x = Axis.1, y = Axis.2)) +
geom_point(aes(colour = ATTRIBUTE_Branch_Letter), size=2) +
#scale_color_manual(values=Sp.colors)+
#geom_text(label = rownames(scores), nudge_x = 0.05, nudge_y = 0.05,check_overlap = T) +
# stat_ellipse(aes(x = Axis.1, y = Axis.2, colour = ATTRIBUTE_Colony_number), linetype = 2) +
ggtitle("PCoA Between Branches 984") +
theme_classic();Branch984_plot
Plot all Colonies in same plot
###### All plots together
Branch945_plot<-Branch945_plot+ theme(legend.position = "none") #remove legend
Branch957_plot<-Branch957_plot+ theme(legend.position = "none") #remove legend
Branch959_plot<-Branch959_plot+ theme(legend.position = "none") #remove legend
Branch960_plot<-Branch960_plot+ theme(legend.position = "none") #remove legend
Branch961_plot<-Branch961_plot+ theme(legend.position = "none") #remove legend
Branch962_plot<-Branch962_plot+ theme(legend.position = "none") #remove legend
Branch963_plot<-Branch963_plot+ theme(legend.position = "none") #remove legend
Branch964_plot<-Branch964_plot+ theme(legend.position = "none") #remove legend
Branch965_plot<-Branch965_plot+ theme(legend.position = "none") #remove legend
Branch966_plot<-Branch966_plot+ theme(legend.position = "none") #remove legend
Branch967_plot<-Branch967_plot+ theme(legend.position = "none") #remove legend
Branch968_plot<-Branch968_plot+ theme(legend.position = "none") #remove legend
Branch969_plot<-Branch969_plot+ theme(legend.position = "none") #remove legend
Branch971_plot<-Branch971_plot+ theme(legend.position = "none") #remove legend
Branch974_plot<-Branch974_plot+ theme(legend.position = "none") #remove legend
Branch976_plot<-Branch976_plot+ theme(legend.position = "none") #remove legend
Branch978_plot<-Branch978_plot+ theme(legend.position = "none") #remove legend
Branch983_plot<-Branch983_plot+ theme(legend.position = "none") #remove legend
Branch984_plot<-Branch984_plot+ theme(legend.position = "none") #remove legend
grid.arrange(Branch945_plot, Branch957_plot, Branch959_plot,Branch960_plot,
Branch961_plot,Branch962_plot,Branch963_plot,Branch964_plot,
Branch965_plot,Branch966_plot,Branch967_plot,Branch968_plot,
Branch969_plot,Branch971_plot,Branch974_plot,Branch976_plot,
Branch978_plot,Branch983_plot,Branch984_plot,nrow = 5)